Project Grant 2553012

This Engineering Research Initiation (ERI) award of $200,000, funded by the National Science Foundation's Division of Civil, Mechanical, and Manufacturing Innovation (CFDA 47.041) and awarded to the University of North Florida beginning July 1, 2026, will develop an integrated quality-control system to reduce defects in laser powder bed fusion (LPBF) additive manufacturing. The primary deliverables include a lightweight computer vision model capable of detecting and quantifying recoater streaks within 0.1 seconds per layer, a layer-aware digital twin implemented as a fast hybrid surrogate that maps streak features to porosity-risk predictions, and a decision-support interface that evaluates candidate repair actions based on predicted risk reduction and time costs. These technical solutions address a critical manufacturing challenge where recoater-induced streaks trigger porosity and incomplete melting, leading to build failures and increased material waste in aerospace, biomedical, and energy applications.

In addition to the core technical development, the project will deliver educational and workforce development products, including course modules and laboratory exercises focused on data-centric manufacturing practices for student training. The award includes outreach activities with regional manufacturers and community colleges designed to accelerate adoption of modern quality practices and expand participation in advanced manufacturing education. The two-year project period concludes on June 30, 2028.